{"id":"W2100947941","doi":"10.1109/lgrs.2010.2085417","title":"C-Band Cross-Polarization Wind Speed Retrieval","year":2010,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":234,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Canadian Space Agency","keywords":"Synthetic aperture radar; Remote sensing; Wind speed; Polarization (electrochemistry); Backscatter (email); C band; Environmental science; L band; Meteorology; Wind direction; Radar; Wind wave; Geology; Physics; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004794984,0.0001999544,0.0001806908,0.0001481444,0.0007127229,0.0004485277,0.0001413323,0.0001339436,0.00003180519],"category_scores_gemma":[0.00009054993,0.0001590846,0.00005906607,0.0004227714,0.0008162299,0.0003825733,0.000009684461,0.0004115708,0.00004667122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003881439,"about_ca_system_score_gemma":0.00004132456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693368,"about_ca_topic_score_gemma":0.0002400229,"domain_scores_codex":[0.9982938,0.00004465978,0.0002419503,0.0005063169,0.0003858352,0.0005274687],"domain_scores_gemma":[0.9992744,0.00008636819,0.0001116332,0.0002513793,0.00005567227,0.0002205755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006604521,0.000005812507,0.009182515,0.00002136753,0.00001043206,0.0001324431,0.0003994544,0.001713823,0.8075832,0.000002151443,0.0001841389,0.1806987],"study_design_scores_gemma":[0.0005906392,0.0001274637,0.2747321,0.00007447853,0.00002961328,0.0009027809,0.00009294313,0.6994569,0.02008067,0.0003382521,0.002883026,0.0006911808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924377,0.0000316038,0.0007930322,0.001319961,0.004304592,0.0001160781,0.000008031931,0.00006260297,0.0009264079],"genre_scores_gemma":[0.9878981,0.00001997743,0.008877164,0.002010975,0.000602,1.058642e-11,0.00001448714,0.000007738809,0.0005695941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7875025,"threshold_uncertainty_score":0.6487283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009177936705272324,"score_gpt":0.2199983973610022,"score_spread":0.2108204606557298,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}